Systems and methods for analyzing pathologies utilizing quantitative imaging are presented herein. Advantageously, the systems and methods of the present disclosure utilize a hierarchical analytics framework that identifies and quantify biological properties/analytes from imaging data and then identifies and characterizes one or more pathologies based on the quantified biological properties/analytes. This hierarchical approach of using imaging to examine underlying biology as an intermediary to assessing pathology provides many analytic and processing advantages over systems and methods that are configured to directly determine and characterize pathology from underlying imaging data.

Methods and systems are provided for generating quantitative computed tomography (CT) angiographic images using imaging systems that acquire a set of projection views forming CT angiographic image data of a patient using a projection duration of less than 50 milliseconds. The method may include producing a composite image from the CT angiographic image data that indicates an attenuation value at each composite image pixel of the patient, backprojecting each projection view in the CT angiographic image data and weighting a value backprojected into at image pixel by an attenuation value of a corresponding pixel in the composite image and summing backprojected values for each image pixel to produce a CT image of the patient. The method may further include performing a scatter correction and determining at least one of a flow direction or a velocity of flow with a vessel in the patient to provide the quantitative CT angiographic images.

A computer implemented method for assessing an arterio-venous malformation (AVM) may include, for example, receiving a patient-specific model of a portion of an anatomy of a patient; using a computer processor to analyze the patient-specific model for identifying one or more blood vessels associated with the AVM, in the patient-specific model; and estimating a risk of an undesirable outcome caused by the AVM, by performing computer simulations of blood flow through the one or more blood vessels associated with the AVM in the patient-specific model.

Computed tomography perfusion (CTP) is used in a method to identify cancerous lesions having genetic mutations and treat them accordingly. Also, CTP values are used to distinguish primary versus metastatic lesions. For example, pulmonary blood flow is identified as one biomarker for EGFR and KRAS genetic mutations in lung cancer, lesion having dual-input pulmonary blood flow exceeding a threshold (e.g., 103 ml/min/100 mL with sensitivity 100% and specificity 62%) are determined as having mutations. The CTP values are calculated using a lesion region-of-interest (ROI) placed to include the area of maximum perfusion intensity within the lesion base and surrounding blush, while avoiding regions of perfusion inhomogeneity (e.g., due to necrosis). In certain implementations, instead of a binary determination, the method can generate probabilities associated with respective alternatives (e.g., mutation/non-nutation and/or primary/secondary), and the method can use multivariable statistical analysis that incorporates patient and/or medical information in addition to CTP values.

The invention relates to a method of detecting symptoms of peritonitis, wherein the method comprises the following steps: taking a photo of a drainage solution and/or of a catheter exit site using a smartphone and/or inputting at least one query parameter which is input by a patient through the input zone of a smartphone; and, evaluating the photo and/or the query parameter.

Provided is a device that transmits and receives an ultrasonic wave to and from an entire periphery of a specimen while preventing a movement of the specimen. An ultrasonic wave transmission and reception device includes: an oscillator array that is arrayed with an oscillator, the oscillator transmitting and receiving an ultrasonic wave; a fixing tool that is disposed between the oscillator array and the specimen and retains the specimen; and a drive mechanism that presses at least a part of the fixing tool against the specimen as to retain the specimen. An ultrasonic wave transmitted by the oscillator array passes through the fixing tool and irradiates on the specimen, and as for the oscillator array, the oscillator array and the fixing tool are disposed in a positional relationship such that the ultrasonic wave reflected by and/or passing through by the specimen and passing through the fixing tool is received.

A method is provided for flow analysis in a target volume of a moving organ, which involves a sequence of first volumetric image data sets that include structural information and three-directional velocity information of the target volume and a sequence of second volumetric image data sets that include structural information of the target volume. The method involves tracking a feature of interest within the sequence of the second volumetric data sets, determining time varying spatial orientation of a plane containing the feature of interest in the sequence of the first volumetric image data sets by transferring the plane from the second volumetric image data sets to the first volumetric image data sets, reformatting the three-directional velocity information into one-directional velocity information on the plane, and performing bi-dimensional quantitative flow analysis using the one-directional velocity information. A corresponding apparatus and computer program are also disclosed and claimed.

The present application relates to a method and system for analyzing blood flow conditions. The method includes: obtaining images at multiple time phases; constructing multiple vascular models corresponding to the multiple time phases; correlating the multiple vascular models; setting boundary conditions of the multiple vascular models respectively based on the result of correlation; and determining condition of blood vessel of the vascular models.

A correction coefficient k is generated based on a combination of a luminance value I constituting a tomographic image F1 and a power value P constituting a power image F2. The power value P is suppressed by multiplying the power value P by the correction coefficient k. After such pre-processing, any one of the color data set (R1, G1, B1) corresponding to the luminance value I and the color data set (R2, G2, B2) corresponding to the power value P (after suppression) is selected.

Systems and methods for establishing an expected benefit from a patient's pharmaceutical use are provided. A neural network is trained on a dataset of medical images, such as ultrasound images, that are tagged with information concerning the expected benefit of the pharmaceutical by people who were imaged to produce the medical images. The trained neural network can then be provided with medical images of a patient, and the neural network can then make a determination as to the expected benefit from a patient's pharmaceutical use.